kangar00: Kernel Approaches for Nonlinear Genetic Association Regression (original) (raw)
Methods to extract information on pathways, genes and various single-nucleotid polymorphisms (SNPs) from online databases. It provides functions for data preparation and evaluation of genetic influence on a binary outcome using the logistic kernel machine test (LKMT). Three different kernel functions are offered to analyze genotype information in this variance component test: A linear kernel, a size-adjusted kernel and a network-based kernel).
| Version: | 1.4.2 |
|---|---|
| Depends: | R (≥ 3.5.0) |
| Imports: | methods, bigmemory, sqldf, CompQuadForm, data.table, lattice, igraph |
| Suggests: | biomaRt, KEGGgraph, testthat |
| Published: | 2024-05-09 |
| DOI: | 10.32614/CRAN.package.kangar00 |
| Author: | Juliane Manitz [aut, cre], Benjamin Hofner [aut], Stefanie Friedrichs [aut], Patricia Burger [aut], Ngoc Thuy Ha [aut], Saskia Freytag [ctb], Heike Bickeboeller [ctb] |
| Maintainer: | Juliane Manitz |
| BugReports: | https://github.com/jmanitz/kangar00/issues |
| License: | GPL-2 |
| URL: | https://kangar00.manitz.org/ |
| NeedsCompilation: | no |
| Citation: | kangar00 citation info |
| CRAN checks: | kangar00 results |
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